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A VUCA (volatile, unpredictable, complex, and ambiguous) environment will be the norm for the foreseeable future. That poses an interesting comparison between the way organizations hedge financial risk and how they might use human capital as a hedge.

A diverse portfolio of investments includes some that do well during economic prosperity, some that are stable under all conditions, and some that do better in economic downturns. When the actual future emerges, one of the assets turns out to be the right bet, and the others do less well. That is the price for diversification and risk hedging. With assumptions about the likelihood of future scenarios, and the payoff of different asset classes in each scenario, finance models can identify a portfolio to achieve a certain return while minimizing risk and volatility.

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With talent, organizations might choose to “stay the course” (keep doing what they did before with their talent and hope it works), “bet on the most likely future” (build talent to fit the most probable scenario), or go generic (invest in such talent attributes as intelligence that apply to many different future situations). Yet these scenarios don’t tap the power of diversification. Talent diversification would build distinct talent assets for each future scenario. If there is a 60% chance that emerging countries will comprise 70% of your revenue in five years, versus a 40% chance that developed countries will comprise that amount of revenue, diversification would suggest building some talent suited for emerging countries and some talent suitable for developed countries. Indeed, if you estimate the payoff of each type of talent under each scenario, you can calculate the proportion of each that will achieve a certain return at minimal risk.

The most frequent question I get from CFOs when I suggest these analogies between talent and financial portfolios is, “When the actual future emerges, what do we do with the talent that doesn’t fit?” The desire to avoid having to liquidate or repurpose talent that doesn’t fit often leads organizations to yet another strategy: hire and develop talent that possesses “learning agility” — focused on goal setting, “thinking about thinking,” and openness to experience — and expect it to adjust once the future becomes clear.

I liken this strategy to “day trading.” It requires the ability to identify agile learners and create a talent system and environment to allow fast changes. Like day trading, using learning agility to solve the uncertainty problem requires its own very significant investment.

While appealing, the idea of addressing uncertainty with learning agility must be considered in light of research that suggests we have much to learn about what learning agility is and how to predict it. A forthcoming article in the journal Industrial and Organizational Psychology that examines learning agility notes that research on the topic is relatively sparse and not uniformly encouraging. Authors Scott DeRue, Susan Ashford, and Christopher Myers of the University of Michigan present a technical analysis of the most well-known measure of learning agility, suggest some concerns about what it actually measures, and encourage more clarity in the definition.

Yes, disposing of a nonperforming financial asset is easier than laying off or retraining talent. But the potential opportunity cost to organizations that don’t diversify their talent portfolios can be immense. Before assuming that learning agility allows day trading in talent, perhaps consider when it is worth investing in multiple talent assets for multiple futures, and investing in talent systems that create effective transitions for your nonperforming talent assets.

John Boudreau is a professor and research director at the University of Southern California’s Marshall School of Business and Center for Effective Organizations, and is co-author of Retooling HR.